1. Field of the Invention
The present invention relates generally to radar signal processing methods for enhancing target detection in clutter and, in particular, to an uncorrelated clutter return cancellation technique using sample ambiguity function measurements.
2. Discussion of the Related Art
Wideband randomly-modulated radar signal waveforms offer a number of advantages for many radar applications. A radar waveform having random modulation of a known bandwidth centered about a carrier frequency has application to conventional pulsed Doppler radar receiver structures such as pulse compressors in combination with cross-correlation circuits for correlating a reconstructed copy of the transmitted modulation with the radar return signal.
The radar ambiguity function is a mathematical concept that provides a measure of the xe2x80x9cambiguityxe2x80x9d inherent in a radar modulation waveform with respect to the radar return signal time delay intervals (target range xe2x80x9ccellsxe2x80x9d) and Doppler frequency shifts (target velocity xe2x80x9ccellsxe2x80x9d) of interest. In the context of a specific target and interference environment that includes clutter interference, the xe2x80x9cgoodness criteriaxe2x80x9d of a radar modulation waveform are generally based on the radar system""s capability to distinguish the differences superimposed by two or more targets on their respective reflected radar signal components. One such criterion is the xe2x80x9cmean square departurexe2x80x9d of the modulated waveform from its shifted self in time and frequency. This criterion can be expressed as a squared magnitude of the two-dimensional autocorrelation function that is well-known in the art as the radar ambiguity function.
The radar ambiguity function can be appreciated as a surface above the target range-velocity (time delay-Doppler shift) plane. The height of such a surface is a measure of the ambiguity (or interference) generated by the radar modulation waveform at a point displaced from a target""s true position and true Doppler shift by an amount equal to the corresponding coordinates oh the target range-velocity plane. Conversely, the radar ambiguity function predicts the interference created at the range-velocity cell location of a desired signal by an undesired target located at a range and velocity offset equivalent to the corresponding coordinates on the target range-velocity plane.
The ambiguity function is commonly used by modulation waveform designers to describe the resolution and interference problems anticipated for a particular modulation waveform. The ideal ambiguity function is known in the art as the xe2x80x9cthumbtackxe2x80x9d, which simultaneously provides both good Doppler and good range target resolution (see, e.g. FIG. 4A). The ambiguity function for a randomly-modulated waveform is a random function whose mean value represents the spike at the center of the xe2x80x9cthumbtackxe2x80x9d ambiguity surface known in the art. The mean squared value of the radar ambiguity function determines the degree to which distributed scattering surfaces (clutter) will cause interference in potential target range-velocity cells over the range-velocity plane. Refer to, for example, Barton et al., xe2x80x9cRadar Evaluation Handbookxe2x80x9d, Artech House, Norwood, Mass., 1991, for additional teachings of the related art.
The randomly-modulated radar signal waveform has attractive features for radar operation in hostile environments but introduces new and unique clutter problems. Clutter analysis has shown that the baseline random modulation waveform is severely clutter limited. Such signal clutter can be described as two components. First, the correlated clutter component results from the radar return signal at the range corresponding to the reference range gate. Secondly, the signal-induced clutter component arises because of modulation that occurs at ranges other than the correlated range gate. This second component is uncorrelated with respect to the randomly-modulated radar reference signal used in the cross-correlation detection process.
The first correlated clutter component is similar to the clutter signal found in range-gated airborne radars using non-random modulation and has a clutter spectrum shaped by the antenna pattern and Doppler distribution. The second uncorrelated component exhibits a flat power spectral density and appears as an increase in total detection noise level. This noise level increase appears as a pedestal on the ambiguity surface (see, e.g. FIG. 4B) at an elevation corresponding to the variance of the random signal-induced clutter noise. Thus, clutter, which can include deception and jamming signals, at Doppler frequencies separated from the target Doppler can introduce an uncorrelated noise level in the target cell much larger than the correlated signal received from targets of interest.
This signal-induced uncorrelated clutter noise effect does not occur in conventional non-random modulation radar designs and is a direct result of the randomly-modulated signal reflections from scatterers at ranges other than the target range. The typical application of a randomly-modulated signal radar employs bandwidths of 500 MHz or more to obtain correspondingly refined range resolution. Thus, the uncorrelated clutter noise power is seen to be much greater than the power of the first correlated clutter component, which is equivalent to the clutter levels known for non-random modulated radar systems.
Most conventional radar clutter rejection methods rely on the correlated properties of the received clutter signals. Correlated clutter can be suppressed by conventional Doppler-processing techniques known in the art, which exploit the correlation (power spectral density function) of the received signal. Such techniques include moving target indicator (MTI), pre-whitening and/or bandpass filters. Such filters can be made adaptive to the shape of the received signal spectrum by including means for estimating characteristics of the clutter environment and dynamically adjusting the filter characteristics accordingly. However, correlated clutter suppression techniques known in the art are ineffective in reducing the uncorrelated clutter components arising from randomly-modulated signal-induced noise. Since the uncorrelated noise has a uniformly flat Doppler spectrum (equivalent to the variance of the random modulation function), known filters that exploit the correlation or shape of the frequency response spectrum cannot reduce the level of this random signal-induced noise term.
The matched filter receiver has been known in the art since the 1940""s. All matched filter receivers correlate the received signal with a reference copy of the transmitted signal. For instance, in U.S. Pat. No. 4,891,649, Labaar et al. disclose a method for achieving a xe2x80x9ccoherent-on-receivexe2x80x9d RF receiver by storing a reference copy of the transmitted signal for use in a correlation receiver. Similarly, in U.S. Pat. No. 4,882,668, Hans-Peter Schmid et al. disclose an adaptive matched filter for extracting known signals from intense noise fields using a form of correlation. Neither of these basic ideas address the problem of canceling uncorrelated clutter signal because such filtering is ineffective for the reasons discussed above.
In U.S. Pat. No. 4,742,353, D""Addio et al. disclose an adaptive filter approach to clutter cancellation. Their method estimates parameters for an assumed signal and clutter model that adjusts filter response characteristics to increase signal-to-noise ratio (SNR). The disclosed filter discriminates signals on the basis of Doppler frequency shift. Because signal-induced clutter has a uniformly flat power spectral density, Doppler filtering approaches such as this are ineffective for reducing such uncorrelated noise.
In U.S. Pat. No. 4,931,800, Ward discloses a compensation method for a moving target detector that removes the effects of pulse stagger during transmission. Other practitioners in the art have addressed problems related to clutter cancellation for non-random and random modulation radar systems but none have proposed a method for canceling the uncorrelated random signal-induced clutter components that are unique to randomly-modulated signal radars. Refer to U.S. Pat. Nos. 3,668,702, 3,710,387 and 3,938,145 for additional teachings representative of efforts in the art to improve clutter cancellation in pulsed Doppler radar systems.
There has not previously been any viable means for reducing the randomly-modulated signal-induced clutter components arising from clutter at ranges other than the correlated gate range, despite the very high levels of this noise in randomly-modulated signal radars. This unresolved problem is clearly felt in the art and is solved by this invention in the manner described below.
The present method for canceling the signal-induced clutter noise requires an estimate of the autocorrelation function of the transmitted randomly-modulated signal. The sample ambiguity function is measured for each transmission pulse by calculating the autocorrelation function for a stored copy of the transmitted randomly-modulated signal. This measured autocorrelation function is then processed using a Doppler processor (such as a Fast-Fourier-Transform (FFT) Processor) matched to the radar Doppler processor used in the radar receiver. The corresponding ambiguity function created by the Doppler processor is the exact power spectral density of the transmitted randomly-modulated signal over a selected region of the range-velocity plane.
The next step in this cancellation method is to estimate clutter backscatter sources by calculating the amplitude and phase of the radar signal returns occurring in detection cells that correspond to stationary scatterers. By looking for large signal peaks in the received signal Doppler filter bank, the system of this invention can identify the location of the stationary scatterers whose clutter contribution is to be canceled. The large signal peaks from the received signal Doppler filter bank are then combined with the measured modulation ambiguity function to obtain an estimate of the stationary clutter contribution to the noise in each target resolution cell.
Finally, the estimated clutter noise power in each cell is subtracted to produce a clutter-canceled power level in each. The clutter source signal and modulation spectral density (ambiguity function) can be combined according to a weighting algorithm based on the Maximum Likelihood Principle using a priori knowledge of antenna parameters if desired. Also, the combination can be made adaptive through the use of a suitable gradient search algorithm to minimize the residual noise level in the target cell. Both the Maximum Likelihood Principal and suitable examples of gradient search algorithms are known in the art.